The goal of the proposal is to explore the strategies used by the central nervous system when manipulating hand- held objects. Recently we developed a new mathematical method of inverse optimization - the 'Analytic Inverse Optimization' (ANIO) method -that allows for reconstructing unknown cost functions (CF) from experimental recordings (Terekhov et al. 2010). The first line of research will deal with the further development of the method and its application to human prehension. Experiment 1-A will explore whether all performers use CFs of the same class. Experiment 1-B will test whether the ANIO method yields estimates of the CFs that are reproducible over protracted periods of time. Experiment 1-C will explore the dependence of the CF class of functions on the number of fingers involved in the task. Experiment 1-D will address interaction between the optimization and variability in multi-finger prehension. The second line of research is based on previous results obtained in our lab and is intended to test the following hypotheses: Experiment 2-A will test the additivity hypothesis: suppose that the digit forces are affected by factors A, B, C, etc. The hypothesis assumes that the effects of the neural commands associated with the above factors are additive. In statistical terms it means that the effects of the factors are significant while their interactions are not. Experiment 2B extends the additivity hypothesis to the complex dynamic tasks. We expect to find that the pattern of grasping force changes as a sum of the effects of two commands associated with the movements along and normal to grasp direction, respectively. Experiment 2C will deal with testing a template control hypothesis according to which for every given combination of the object geometry and local friction the performers select a digit force pattern ('template') and then scale the digit forces with the load force. Experiment 2- D will consist of two parts in which effects of one finger fatigue or fatigue of all fingers will be explored. The goal is to test whether the fatigued finger exerts the same %% of its current maximal force as it did prior to fatigue. Essentially, the experiment will explore the 'robustness' of prehension control, using local fatigue as a perturbation tool. Under 'robustness' we understand ability to perform a task when performance potential of one of the contributing elements is diminished.